Structural Health Monitoring of RC structures using optic fiber strain measurements: a deep learning approach
Paper in proceeding, 2019

This paper reports the early findings of an ongoing project aimed at developing new methods to upgrade the current maintenance strategies of the civil and transport infrastructure. As part of these new methods, the use of Machine Learning (ML) algorithms is being investigated to constitute the core of a new generation of more accurate and robust structural health monitoring (SHM) systems for concrete structures. Unlike most of the existing SHM systems, relying on the analysis of the natural frequencies of the structure based on data obtained from accelerometers, the present study uses a distributed optic fiber system to monitor the strain distribution along steel reinforcing bars. The preliminary results of the study indicate that a semi-supervised Deep Autoencoder algorithm (DAE) can successfully quantify the damage attributable to transverse cracks in a reinforced concrete beam subjected to three-point loading. Future applications will feature the determination of crack locations, early detection of reinforcement corrosion as well as other types of damage such as splitting cracks or surface spalling.

concrete structures

distributed optic fiber.

structural health monitoring

machine learning

anomaly detection

deep autoencoders

Author

Dimitrios Karypidis

Chalmers, Architecture and Civil Engineering, Structural Engineering

Carlos Gil Berrocal

Chalmers, Architecture and Civil Engineering, Structural Engineering

Rasmus Rempling

Chalmers, Architecture and Civil Engineering, Structural Engineering

Mats Granath

University of Gothenburg

Peter Simonsson

Swedish Transport Administration

20th Congress of IABSE, New York City 2019: The Evolving Metropolis - Report

Vol. 114
978-385748165-9 (ISBN)

2019 IABSE Congress New York City - The Evolving Metropolis
New York City, USA,

SensIT - Sensor driven cloud-based strategies for infrastructure management

WSP Sverige, 2018-07-01 -- 2020-08-31.

Microsoft Research, 2018-07-01 -- 2020-08-31.

Thomas Concrete Group, 2018-07-01 -- 2020-08-31.

NCC AB, 2018-07-01 -- 2020-08-31.

Swedish Transport Administration (2018/27871), 2018-07-01 -- 2020-08-31.

Driving Forces

Sustainable development

Innovation and entrepreneurship

Areas of Advance

Building Futures (2010-2018)

Subject Categories

Civil Engineering

Infrastructure Engineering

More information

Latest update

3/21/2023